ESRC DTP Collaborative Studentship: International Collaboration on the Health Economic Evaluation of Health Screening

Economic models play a critical role in informing health screening policies by evaluating cost-effectiveness, feasibility, and long-term impact. However, their complexity often limits their practical application, as policymakers may struggle with their interpretation and implementation. A lack of standardized interpretation frameworks, clear articulation of assumptions and uncertainties, and user-friendly communication tools can hinder the effective use of economic insights in decision-making. This research will contribute to a more transparent, equitable, and effective approach to health screening decision-making in the UK. It will explore novel ways to convey economic model structures through interactive tools and improved reporting frameworks.

This PhD will include four unique elements:
1. A scoping review to assess existing tools designed to facilitate evidence-based decision-making in the context of complex quantitative evidence.
2. The development of a prototype interactive tool to communicate the methods and results of an economic model, applying it to a UK National Screening Committee (NSC) case study.
3. Stakeholder evaluation through interviews with decisionmakers and non-health economists to assess the tool's effectiveness in improving understanding and informing better decision-making.
4. Development of recommendations based on findings ensuring their effective integration into decision-making processes.

The methodology and techniques to be employed:
1. A scoping review to identify existing decision-support tools and assess their applicability to economic models.
2. Model development and case study application to design an interactive economic model relevant to a UK NSC screening programme.
3. Qualitative research using semi-structured interviews with stakeholders to evaluate the usability and impact of the interactive tool.
4. Development of recommendations based on findings ensuring their effective integration into decision-making processes.